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Computer Science > Data Structures and Algorithms

Title:A Short Survey on Data Clustering Algorithms

Abstract: With rapidly increasing data, clustering algorithms are important tools for
data analytics in modern research. They have been successfully applied to a
wide range of domains; for instance, bioinformatics, speech recognition, and
financial analysis. Formally speaking, given a set of data instances, a
clustering algorithm is expected to divide the set of data instances into the
subsets which maximize the intra-subset similarity and inter-subset
dissimilarity, where a similarity measure is defined beforehand. In this work,
the state-of-the-arts clustering algorithms are reviewed from design concept to
methodology; Different clustering paradigms are discussed. Advanced clustering
algorithms are also discussed. After that, the existing clustering evaluation
metrics are reviewed. A summary with future insights is provided at the end.